Document Detail


Comparison of breast tissue measurements using magnetic resonance imaging, digital mammography and a mathematical algorithm.
MedLine Citation:
PMID:  23044556     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Women with mostly mammographically dense fibroglandular tissue (breast density, BD) have a four- to six-fold increased risk for breast cancer compared to women with little BD. BD is most frequently estimated from two-dimensional (2D) views of mammograms by a histogram segmentation approach (HSM) and more recently by a mathematical algorithm consisting of mammographic imaging parameters (MATH). Two non-invasive clinical magnetic resonance imaging (MRI) protocols: 3D gradient-echo (3DGRE) and short tau inversion recovery (STIR) were modified for 3D volumetric reconstruction of the breast for measuring fatty and fibroglandular tissue volumes by a Gaussian-distribution curve-fitting algorithm. Replicate breast exams (N = 2 to 7 replicates in six women) by 3DGRE and STIR were highly reproducible for all tissue-volume estimates (coefficients of variation <5%). Reliability studies compared measurements from four methods, 3DGRE, STIR, HSM, and MATH (N = 95 women) by linear regression and intra-class correlation (ICC) analyses. Rsqr, regression slopes, and ICC, respectively, were (1) 0.76-0.86, 0.8-1.1, and 0.87-0.92 for %-gland tissue, (2) 0.72-0.82, 0.64-0.96, and 0.77-0.91, for glandular volume, (3) 0.87-0.98, 0.94-1.07, and 0.89-0.99, for fat volume, and (4) 0.89-0.98, 0.94-1.00, and 0.89-0.98, for total breast volume. For all values estimated, the correlation was stronger for comparisons between the two MRI than between each MRI versus mammography, and between each MRI versus MATH data than between each MRI versus HSM data. All ICC values were >0.75 indicating that all four methods were reliable for measuring BD and that the mathematical algorithm and the two complimentary non-invasive MRI protocols could objectively and reliably estimate different types of breast tissues.
Authors:
Lee-Jane W Lu; Thomas K Nishino; Raleigh F Johnson; Fatima Nayeem; Donald G Brunder; Hyunsu Ju; Morton H Leonard; James J Grady; Tuenchit Khamapirad
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Publication Detail:
Type:  Comparative Study; Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.     Date:  2012-10-09
Journal Detail:
Title:  Physics in medicine and biology     Volume:  57     ISSN:  1361-6560     ISO Abbreviation:  Phys Med Biol     Publication Date:  2012 Nov 
Date Detail:
Created Date:  2012-10-17     Completed Date:  2013-03-18     Revised Date:  2013-11-14    
Medline Journal Info:
Nlm Unique ID:  0401220     Medline TA:  Phys Med Biol     Country:  England    
Other Details:
Languages:  eng     Pagination:  6903-27     Citation Subset:  IM    
Affiliation:
Department of Preventative Medicine and Community Health, The University of Texas Medical Branch, Galveston, TX 77555-1109, USA.
Data Bank Information
Bank Name/Acc. No.:
ClinicalTrials.gov/NCT00204477;  NCT00204490
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Breast / cytology*
Female
Humans
Imaging, Three-Dimensional
Magnetic Resonance Imaging / methods*
Mammography / methods*
Radiographic Image Enhancement / methods*
Regression Analysis
Reproducibility of Results
Grant Support
ID/Acronym/Agency:
2 P30 ES06676/ES/NIEHS NIH HHS; CA65628/CA/NCI NIH HHS; M01 RR000073/RR/NCRR NIH HHS; P30 ES006676/ES/NIEHS NIH HHS; R01 CA095545/CA/NCI NIH HHS; R01 CA95545/CA/NCI NIH HHS; UL1 RR029876/RR/NCRR NIH HHS; UL1 TR000071/TR/NCATS NIH HHS; UL1RR029876/RR/NCRR NIH HHS
Comments/Corrections

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